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GEO Checker

How likely is a site to be cited by ChatGPT, Claude, Gemini, Grok or Perplexity, and can a shopping agent like Muse buy from it?

What the GEO Checker measures

  • GEO Score

    Site readiness, lifted by what assistants already know. Fame can only add; an unknown business keeps the score its pages earn.

  • Site readiness

    Twelve checks on every page read.

  • Recognition

    What assistants already know.

  • Agent readiness

    Is this the store the agent picks?

  • Access

    Can an assistant get the page at all? robots.txt for the AI search and live-fetch crawlers, noindex, the canonical, the sitemap, and whether the content exists before JavaScript runs — the crawlers of OpenAI, Anthropic and Perplexity do not run it. A gate, not a merit: scored as its weakest check, and left out of the score when nothing is wrong.

  • Structure

    Can it parse what it got? Structured data (an Organization plus a type that says what the page is), one H1 and H2 sections, question headings with an answer beneath, landmarks, title, description and Open Graph tags.

  • Substance

    Is there anything worth quoting? Specific claims — years, prices, quantities, places — rather than adjectives any company could use; on an article, a byline, a date and links to sources. Plus a language model’s read of every page: what it could cite, and what the site does not state.

  • Identity

    Can it tell who is behind the site? Organization markup with sameAs links to verified profiles and a logo, an About link, a way to reach a person. On-page signals only — reputation is Recognition’s question.

  • Freshness

    Is it current? The newest date among Last-Modified, <time>, Open Graph and schema dates. Event dates in the future do not count; an undated brand page is fine, an undated article is not.

Why this matters

AI assistants and agents do not rank pages the way a search engine did. They fetch pages with their own crawlers and look for entities, structured data, and citable claims. Optimizing for these signals (Generative Engine Optimization, GEO) is how a brand gets named when a user asks an AI assistant a question.

Example reports